Will Tesla be able to maintain its lead in the EV market for very long?

This is one of the most pressing issues in the American auto sector today. One positive aspect of Tesla is the company's devoted customer base and recognizable name recognition (similar to Apple). It also invests more in research and development per vehicle than its rivals and has a head start in EV production.

Conversely, established automakers like Volkswagen are actively plotting their strategy to surpass Tesla. As the current market leaders, they have decades of experience in the auto industry and are spending billions to catch up.

We've visualized data from the EPA's 2022 Automotive Trends Report to bring you up to speed on this developing story.

Info for the Model Year of 2021

The full production data used in this infographic is for the 2021 model year, but it comes from a report for 2022.

Combined EV and PHEV output is shown in the table below (plug-in hybrid electric vehicle).

It is important to note that Toyota and Stellantis, the two largest legacy automakers in this dataset, only produced PHEVs. Toyota's first electric vehicle, the bZ4X, won't hit the market until 2023.

Stellantis seems to be falling even further behind, despite having enormous unrealized potential in its Jeep and Ram brands. Stellantis CEO Carlos Tavares said in a recent interview that the firm has budgeted $36 billion for electrification and software.

Legacy Brands with the Most Momentum

In the race to develop electric vehicles, some long-standing manufacturers have gotten the jump on their rivals.

Volkswagen, one of these storied manufacturers, has made a significant investment in electric vehicles (EVs) in the wake of the Dieselgate scandal. The company plans to roll out multiple EV models, including the ID.3 hatchback, ID.4 SUV, and ID. Buzz, with the goal of producing 22 million EVs by 2028. (an electric revival of the classic Microbus).

Even Ford is keeping up, having just announced an EV investment of $22 billion between 2021 and 2025. In November of 2022, the company manufactured their 150,000th Mustang Mach-E, and by the end of 2023, they hoped to have 270,000 of them in circulation.

Additionally, over 200,000 F-150 Lightnings have been reserved since Ford announced the truck. The Lightning is scheduled to have a production run of 15,000 in 2022, 55,000 in 2023, and 80,000 in 2024. Ford's main competitor in the electric pickup truck segment, Rivian, is on track to sell 25,000 vehicles by 2022.

And morning water bottle struggles.

Welcome to my TikTok, where I share my stay-at-home life! I'll show you my usual day from morning to night.

I rise early to prepare my guy iced coffee. I make matcha, my favorite drink. I also fill our water bottles, which takes time and effort, so I record and describe the procedure. As you see me perform the unthinkable by putting a water bottle in a soda machine, you'll see my magnificent but unowned condo. My lover has everything, including:

1. In the living room, a sizable velvet alabaster divan. I was unable to use the words white or sofa in place of alabaster or a divan since they are insufficiently elegant and do not adequately convey how opulent the item is. The price tag on the divan was another huge feature; I'm sure my lover wouldn't purchase any furniture for less than $20k because it would be beneath him.

2. A plush Swiss coffee-colored Tabriz carpet. Once more, white is a color associated with the underclass; for us, the wealthy, it's alabaster or swiss coffee. Sorry, my boyfriend is wealthy; I'm truly in the same situation. And yet, I’m the one whos freeloading off of him, not you haha!

3. Soft translucent powder is the hue of the vinyl wallcoverings. I merely made up the name of that hue, but I have to maintain the online character I've established. There is no room for adopting language typical of peasant people; I must reiterate that I am wealthy while they are not.

I rest after filling our water bottles. I'm really fatigued from chores. My boyfriend is skeptical about hiring a housekeeper and cook. Does he assume I'm a servant or maid? I can't be overly demanding or throw a tantrum since he may replace me with a younger version. Leonardo Di Caprio's fault!

After the break, I bring my lover a water bottle. He's off to work with my best wishes. After cleaning the shower, I text my BF saying I broke a nail. He charged $675 for a crystal-topped shellac manicure. Lucky me!

After this morning's crazy choirs, especially the water bottle one, I'm famished. I dress quickly and go to the neighborhood organic-vegan-gluten-free-sugar-free-plasma-free-GMO-free-HBO-free breakfast place. Most folks can't afford $17.99 for a caffeine-free-mushroom-plus-mud-and-electrolytes morning beverage. It goes nicely with my matcha. Eggs Benedict cost $68. English muffins are off-limits. I can't make myself obese. My partner said he'd swap me for a 19-year-old Eastern European if I keep eating bacon.

I leave no tip since tipping is too much pressure and math for me, so I go shopping.

My shopping adventures have gotten monotonous. 47 designer bags and 114 bag covers Birkins need their own luggage. My babies! I've never caught my BF with a baby. I have sleeping medications and a turkey baster. Tatiana is much younger and thinner than me, so I can't lose him to her. The goal is to become a stay-at-home wife shortly. A turkey baster is essential.

After spending $955 on La Mer lotions and getting a crystal manicure, I nap. Before my boyfriend's return, I can nap for 5 hours.

I wake up around 4 pm — it’s time to prepare dinner. Yes, I said “prepare for dinner,” not “prepare dinner.” I have crystals on my nails! Do you really think I would cook? No way.

My husband's arrival still requires much work. I clean the kitchen, get cutlery and napkins. I order UberEats while my BF is 30-45 minutes away.

Wagyu steaks with Matsutake mushroom soup today. I pick desserts for my lover but not myself. Eastern European threat?

When my BF gets home from work, we eat. I don't believe in tipping UberEats drivers. If he wants to appreciate life's finer things, he should locate a rich woman.

After eating, we plan our getaway. I requested Aruba's fanciest hotel for winter and expect a butler. We're bickering over who gets the butler. We may need two.

Day's end, I'm exhausted. Stay-at-home girlfriends put in a lot of time and work. Work and duties are never-ending.

Before bed, I shower and use a liquid gold mask in my 27-step makeup procedure. It's a French luxury brand, not La Mer.

Here's my day.

Note: I like satire and absurd trends. Stay-at-home-girlfriend TikTok videos have become popular recently.

I don't shame or support such agreements; I'm just an observer. Thanks for reading.

Python Volatility-Based Catapult Indicator

As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.

Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.

The Foundation: Volatility

The Catapult predicts significant changes with the 21-period Relative Volatility Index.

The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.

Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.

Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:

As stated, standard deviation is:

# The function to add a number of columns inside an array
def adder(Data, times):
    
    for i in range(1, times + 1):
    
        new_col = np.zeros((len(Data), 1), dtype = float)
        Data = np.append(Data, new_col, axis = 1)
        
    return Data

# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
    
    for i in range(1, times + 1):
    
        Data = np.delete(Data, index, axis = 1)
        
    return Data
    
# The function to delete a number of rows from the beginning
def jump(Data, jump):
    
    Data = Data[jump:, ]
    
    return Data

# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)

# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)

# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)

# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file

def volatility(Data, lookback, what, where):
    
  for i in range(len(Data)):

     try:

        Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
     except IndexError:
        pass
        
  return Data

The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.

The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.

RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.

def ma(Data, lookback, close, where): 
    
    Data = adder(Data, 1)
    
    for i in range(len(Data)):
           
            try:
                Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                pass
            
    # Cleaning
    Data = jump(Data, lookback)
    
    return Data
def ema(Data, alpha, lookback, what, where):
    
    alpha = alpha / (lookback + 1.0)
    beta  = 1 - alpha
    
    # First value is a simple SMA
    Data = ma(Data, lookback, what, where)
    
    # Calculating first EMA
    Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)    
 
    # Calculating the rest of EMA
    for i in range(lookback + 2, len(Data)):
            try:
                Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
        
            except IndexError:
                pass
            
    return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
    
    # Adding a few columns
    Data = adder(Data, 7)
    
    # Calculating Differences
    for i in range(len(Data)):
        
        Data[i, where] = Data[i, close] - Data[i - width, close]
     
    # Calculating the Up and Down absolute values
    for i in range(len(Data)):
        
        if Data[i, where] > 0:
            
            Data[i, where + 1] = Data[i, where]
            
        elif Data[i, where] < 0:
            
            Data[i, where + 2] = abs(Data[i, where])
            
    # Calculating the Smoothed Moving Average on Up and Down
    absolute values        
                             
    lookback = (lookback * 2) - 1 # From exponential to smoothed
    Data = ema(Data, 2, lookback, where + 1, where + 3)
    Data = ema(Data, 2, lookback, where + 2, where + 4)
    
    # Calculating the Relative Strength
    Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
    
    # Calculate the Relative Strength Index
    Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))  
    
    # Cleaning
    Data = deleter(Data, where, 6)
    Data = jump(Data, lookback)

    return Data

def relative_volatility_index(Data, lookback, close, where):

    # Calculating Volatility
    Data = volatility(Data, lookback, close, where)
    
    # Calculating the RSI on Volatility
    Data = rsi(Data, lookback, where, where + 1) 
    
    # Cleaning
    Data = deleter(Data, where, 1)
    
    return Data

The Arm Section: Speed

The Catapult predicts momentum direction using the 14-period Relative Strength Index.

As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:

• A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.

• When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.

Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.

The direction-finding filter in the frame

The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.

Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.

This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:

We defined the moving average function above. Create the Catapult indication now.

Indicator of the Catapult

The indicator is a healthy mix of the three indicators:

• The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.

• If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.

• The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.

lookback_rvi = 21
lookback_rsi = 14
lookback_ma  = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)

Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.

The chart below shows recent EURUSD hourly values.

def signal(Data, rvi_col, signal):
    
    Data = adder(Data, 10)
        
    for i in range(len(Data)):
            
        if Data[i,     rvi_col] < 30 and \
           Data[i - 1, rvi_col] > 30 and \
           Data[i - 2, rvi_col] > 30 and \
           Data[i - 3, rvi_col] > 30 and \
           Data[i - 4, rvi_col] > 30 and \
           Data[i - 5, rvi_col] > 30:
               
               Data[i, signal] = 1
                           
    return Data

Signals are straightforward. The indicator can be utilized with other methods.

my_data = signal(my_data, 6, 7)

Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.

Summary

To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation. Technical analysis will lose its reputation as subjective and unscientific.

After you find a trading method or approach, follow these steps:

• Put emotions aside and adopt an analytical perspective.

• Test it in the past in conditions and simulations taken from real life.

• Try improving it and performing a forward test if you notice any possibility.

• Transaction charges and any slippage simulation should always be included in your tests.

• Risk management and position sizing should always be included in your tests.

After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.

Cryptoshit. This thing is crazy to buy.

Charlie Munger is revered and powerful in finance.

Munger, vice chairman of Berkshire Hathaway, is noted for his wit, no-nonsense attitude to investment, and ability to spot promising firms and markets.

Munger's crypto views have upset some despite his reputation as a straight shooter.

“There’s only one correct answer for intelligent people, just totally avoid all the people that are promoting it.” — Charlie Munger

The Munger Interview on CNBC (4:48 secs)

This Monday, CNBC co-anchor Rebecca Quick interviewed Munger and brought up his 2007 statement, "I'm not allowed to have an opinion on this subject until I can present the arguments against my viewpoint better than the folks who are supporting it."

Great investing and life advice!

If you can't explain the opposing reasons, you're not informed enough to have an opinion.

In today's world, it's important to grasp both sides of a debate before supporting one.

Rebecca inquired:

Does your Wall Street Journal article on banning cryptocurrency apply? If so, would you like to present the counterarguments?

Mungers reply:

I don't see any viable counterarguments. I think my opponents are idiots, hence there is no sensible argument against my position.

Consider his words.

Do you believe Munger has studied both sides?

He said, "I assume my opponents are idiots, thus there is no sensible argument against my position."

This is worrisome, especially from a guy who once encouraged studying both sides before forming an opinion.

Munger said:

National currencies have benefitted humanity more than almost anything else.

Hang on, I think we located the perpetrator.

Munger thinks crypto will replace currencies.

False.

I doubt he studied cryptocurrencies because the name is deceptive.

He misread a headline as a Dollar destroyer.

Cryptocurrencies are speculations.

Like Tesla, Amazon, Apple, Google, Microsoft, etc.

Crypto won't replace dollars.

In the interview with CNBC, Munger continued:

“I’m not proud of my country for allowing this crap, what I call the cryptoshit. It’s worthless, it’s no good, it’s crazy, it’ll do nothing but harm, it’s anti-social to allow it.” — Charlie Munger

Not entirely inaccurate.

Daily cryptos are established solely to pump and dump regular investors.

Let's get into Munger's crypto aversion.

Rat poison is bitcoin.

Munger famously dubbed Bitcoin rat poison and a speculative bubble that would implode.

Partially.

But the bubble broke. Since 2021, the market has fallen.

Scam currencies and NFTs are being eliminated, which I like.

Whoa.

Why does Munger doubt crypto?

Mungers thinks cryptocurrencies has no intrinsic value.

He worries about crypto fraud and money laundering.

Both are valid issues.

Yet grouping crypto is intellectually dishonest.

Ethereum, Bitcoin, Solana, Chainlink, Flow, and Dogecoin have different purposes and values (not saying they’re all good investments).

Fraudsters who hurt innocents will be punished.

Therefore, complaining is useless.

Why not stop it? Repair rather than complain.

Regrettably, individuals today don't offer solutions.

Blind Areas for Mungers

As with everyone, Mungers' bitcoin views may be impacted by his biases and experiences.

OK.

But Munger has always advocated classic value investing and may be wary of investing in an asset outside his expertise.

Mungers' banking and insurance investments may influence his bitcoin views.

Could a coworker or acquaintance have told him crypto is bad and goes against traditional finance?

Right?

Takeaways

Do you respect Charlie Mungers?

Yes and no, like any investor or individual.

To understand Mungers' bitcoin beliefs, you must be critical.

Mungers is a successful investor, but his views about bitcoin should be considered alongside other viewpoints.

Munger’s success as an investor has made him an influencer in the space.

Influence gives power.

He controls people's thoughts.

Munger's ok. He will always be heard.

I'll do so cautiously.